ArticleBMJ open2018
Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease.
Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- How long does it take to complete and publish a systematic review of animal studies?BMC medical research methodology · 2025Article
- Global research trends and hotspots in the application of lasers for acne treatment from 1986 to 2022: bibliometric and visual analysis.Lasers in medical science · 2025Review
- Manual versus machine: How accurately does the Medical Text Indexer (MTI) classify different document types into disease areas?PloS one · 2024Article
- Preliminary guideline for reporting bibliometric reviews of the biomedical literature (BIBLIO): a minimum requirements.Systematic reviews · 2023Article
- International aspects in healthcare and medical education: Scientometric trends and knowledge maps before the COVID-19 pandemic.Journal of education and health promotion · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveSince most biomedical research focuses on a specific disease, evaluation of research output requires disease-specific bibliometric indicators. Currently used methods are insufficient. The aim of this study is to develop a method that enables detailed analysis of worldwide biomedical research output by disease.
designWe applied text mining techniques and analysis of author keywords to link publications to disease groups. Fractional counting was used to quantify disease-specific biomedical research output of an institution or country. We calculated global market shares of research output as a relative measure of publication volume. We defined 'top publications' as the top 10% most cited publications per disease group worldwide. We used the percentage of publications from an institution or country that were top publications as an indicator of research quality.
resultsWe were able to classify 54% of all 6.5 million biomedical publications in our database (based on Web of Science) to a disease group. We could classify 78% of these publications to a specific institution. We show that between 2000 and 2012,'other infectious diseases' were the largest disease group with 337 485 publications. Lifestyle diseases, cancers and mental disorders have grown most in research output. The USA was responsible for the largest number of top 10% most cited publications per disease group, with a global share of 45%. Iran (+3500%) and China (+700%) have grown most in research volume.
conclusionsThe proposed method provides a tool to assess biomedical research output in new ways. It can be used for evaluation of historical research performance, to support decision-making in management of research portfolios, and to allocate research funding. Furthermore, using this method to link disease-specific research output to burden of disease can contribute to a better understanding of the societal impact of biomedical research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.